摘要
X射线安检工作是地铁安检工作的重要部分。当前X光图片检测工作很大程度上依赖人工来完成。本文采用了一种基于机器学习方法的X光图片禁带品智能识别技术,将区域卷积神经网络框架和VGG16网络模型相结合,能快速精准的在X光图片上完成对禁带品的标记识别。
X-ray security inspection is an important part of Metro security inspection.At present,X-ray image detection depends largely on manual work.In this paper,an intelligent recognition technology of forbidden goods in X-ray images based on machine learning method is introduced.By combining the framework of regional convolution neural network with VGG16 network model,the tag recognition of forbidden goods in X-ray images can be accomplished quickly and accurately.
作者
王玉维
杨波
马卫东
WANG Yu-wei;YANG Bo;MA Wei-dong(Security Department of Beijing Mass Transit Railway Operation Corp Ltd,Beijing;Beijing Telesound Electronics Co Ltd,Beijing)
出处
《中国传媒大学学报（自然科学版）》
2019年第4期71-74,共4页
Journal of Communication University of China：Science and Technology
关键词
机器学习
区域卷积神经网络
地铁安检
深度学习
machine learning
regional convolution neural network
metro security inspection
in-depth learning
